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Modeling and Multivariate Methods - SAS

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Chapter 10 Creating Neural Networks 287<br />

Model Options<br />

Table 10.7 Descriptions of the Training <strong>and</strong> Validation Measures of Fit (Continued)<br />

Mean Abs Dev<br />

Misclassification Rate<br />

-LogLikelihood<br />

SSE<br />

Sum Freq<br />

The average of the absolute values of the differences between the response<br />

<strong>and</strong> the predicted response. When the response is nominal or ordinal, the<br />

differences are between 1 <strong>and</strong> p (the fitted probability for the response level<br />

that actually occurred).<br />

The rate for which the response category with the highest fitted probability<br />

is not the observed category. Appears only when the response is nominal or<br />

ordinal.<br />

Gives the negative of the log likelihood.<br />

Gives the error sums of squares. Available only when the response is<br />

continuous.<br />

Gives the number of observations that are used. If you specified a Freq<br />

variable in the Neural launch window, Sum Freq gives the sum of the<br />

frequency column.<br />

If there are multiple responses, fit statistics are given for each response, <strong>and</strong> an overall Generalized Rsquare<br />

<strong>and</strong> -LogLikelihood is given.<br />

Confusion Statistics<br />

For nominal or ordinal responses, a Confusion Matrix report <strong>and</strong> Confusion Rates report is given. See<br />

Figure 10.5. The Confusion Matrix report shows a two-way classification of the actual response levels <strong>and</strong><br />

the predicted response levels. For a categorical response, the predicted level is the one with the highest<br />

predicted probability. The Confusion Rates report is equal to the Confusion Matrix report, with the<br />

numbers divided by the row totals.<br />

Model Options<br />

Each model report has a red triangle menu containing options for producing additional output or saving<br />

results. Table 10.8 describes the options in the red triangle menus.<br />

Table 10.8 Model Report Options<br />

Diagram<br />

Show Estimates<br />

Profiler<br />

Shows a diagram representing the hidden layer structure.<br />

Shows the parameter estimates in a report.<br />

Launches the Prediction Profiler. For nominal or ordinal responses, each<br />

response level is represented by a separate row in the Prediction Profiler. For<br />

details about the options in the red triangle menu, see the “Visualizing,<br />

Optimizing, <strong>and</strong> Simulating Response Surfaces” chapter on page 553.

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